Areas of expertise
- Autonomous Systems
- Computing, Simulation & Modelling
- Ergonomics, Human Factors, Driver Safety
- Human Factors
- Systems Engineering
- Vehicle Engineering & Mobility
Dr. Yang Xing received his Ph.D. degree from Cranfield University in July 2018. He also holds an MSc degree (with distinction) in Control Systems from the University of Sheffield in 2014. Before joining Cranfield University in 2021, Yang worked as a research associate with the Department of Computer Science at the University of Oxford from 2020 to 2021, and a research fellow with the Department of Mechanical and Aerospace Engineering, at Nanyang Technological University from 2019 to 2020. His research interest focus on artificial intelligence, deep learning, computer vision, human-autonomy collaboration, and autonomous vehicles, where he has contributed 2 books and over 50 papers (including 2 ESI highly cited papers) on high-quality peer-review journals and conferences.
Dr. Yang Xing serves as a Review Editor on Frontiers in Mechanical Engineering, and he was a Guest Editor-in-Cheif/Editor on IEEE Internet of Things Journal, Frontiers in Mechanical Engineering, and IEEE Intelligent Transportation Magazine, etc. He was session chair/co-chair on IEEE SMC 2020, IFAC Workshop on CPHS 2020, and IEEE IV 2018. He won the Best Workshop/Special Session Paper on IEEE IV 2018 and Best Paper on China National Intelligence Technology Conference 2019.
Currently I'm looking for PhD students in the following research areas:
1. Human-autonomy collaboration and teaming.
2. Human behavior modeling for intelligent vehicles.
3. Computer vision for human activity recognition (HAR).
4. Computer vision for autonomous vehicles (including segmentation, object diction, and visual augmentation).
5. Application of machine learning/deep learning in autonomous vehicles.
Articles In Journals
- Xing Y, Lv C, Cao D & Velenis E (2021) Multi-scale driver behavior modeling based on deep spatial-temporal representation for intelligent vehicles, Transportation Research Part C: Emerging Technologies, 130 (September) Article No. 103288.
- Hang P, Lv C, Huang C, Xing Y & Hu Z (2021) Cooperative decision making of connected automated vehicles at multi-lane merging zone: a coalitional game approach, IEEE Transactions on Intelligent Transportation Systems, Available online 2 April 2021.
- Liu T, Xing Y, Tang X, Wang H, Yu H & Wang F (2021) Cyber-physical-social system for parallel driving: from concept to application, IEEE Intelligent Transportation Systems Magazine, 13 (1) 59-69.
- Hu Z, Lv C, Hang P, Huang C & Xing Y (2021) Data-driven estimation of driver attention using calibration-free eye gaze and scene features, IEEE Transactions on Industrial Electronics, Available online 9 February 2021 (2).
- Hang P, Huang C, Hu Z, Xing Y & Lv C (2021) Decision making of connected automated vehicles at an unsignalized roundabout considering personalized driving behaviours, IEEE Transactions on Vehicular Technology, 70 (5) 4051-4064.
- Hang P, Lv C, Xing Y, Huang C & Hu Z (2021) Human-like decision making for autonomous driving: a noncooperative game theoretic approach, IEEE Transactions on Intelligent Transportation Systems, 22 (4) 2076-2087.
- Xing Y (2021) Human-machine adaptive shared control for safe driving under automation degradation, IEEE Intelligent Transportation Systems Magazine, Available online 01 April 2021.
- Xing Y, Lv C, Cao D & Hang P (2021) Toward human-vehicle collaboration: Review and perspectives on human-centered collaborative automated driving, Transportation Research Part C: Emerging Technologies, 128 (July) Article No. 103199.
- Huang C, Chen L, Hang P & Xing Y (2021) Toward safe and personalized autonomous driving: decision-making and motion control with DPF and CDT techniques, IEEE/ASME Transactions on Mechatronics, 26 (2) 611-620.
- Xing Y, Lv C, Wang H, Wang H, Ai Y, Cao D, Velenis E & Wang F-Y (2019) Driver lane change intention inference for intelligent vehicles: framework, survey, and challenges, IEEE Transactions on Vehicular Technology, 68 (6) 5379-5390.
- Lv C, Xing Y, Zhang J, Na X, Li Y, Liu T, Cao D & Wang FY (2018) Levenberg-Marquardt backpropagation training of multilayer neural networks for state estimation of a safety critical cyber-physical system, IEEE Transactions on Industrial Informatics, 14 (8) 3436-3446.
- Xing Y, Lv C, Zhang Z, Wang H, Na X, Cao D, Velenis E & Wang F-Y (2018) Identification and analysis of driver postures for in-vehicle driving activities and secondary tasks recognition, IEEE Transactions on Computational Social Systems, 5 (1) 95-108.
- Lv C, Xing Y, Lu C, Liu Y, Guo H, Gao H & Cao D (2018) Hybrid-learning-based classification and quantitative inference of driver braking intensity of an electrified vehicle, IEEE Transactions on Vehicular Technology, 67 (7) 5718-5729.
- Xing Y, Lv C, Wang H, Cao D, Velenis E & Wang F (2018) Advances in vision-based lane detection: algorithms, integration, assessment, and perspectives on ACP-based parallel vision, IEEE Caa Journal of Automatica Sinica, 5 (3) 645-661.
- Xing Y, Lv C, Wang H, Cao D & Velenis E (2018) Dynamic integration and online evaluation of vision-based lane detection algorithms, IET Intelligent Transport Systems, 13 (1) 55-62.
- Zhao Y, Xing Y, Xing Y, Lv C, Cao D & Wang H (2018) Driver workload estimation using a novel hybrid method of error reduction ratio causality and support vector machine, Measurement, 114 (January) 390-397.
- Yang X, Lv C, Cao D, Velenis E & Wang F (2018) End-to-end driving activities and secondary tasks recognition using deep convolutional neural network and transfer learning. In: 2018 IEEE Intelligent Vehicles Symposium (IV), Changshu, Suzhou, 26-30 June 2018.
- Xing Y, Lv C, Huaji W, Wang H & Cao D (2017) Recognizing driver braking intention with vehicle data using unsupervised learning methods. In: WCX17: SAE World Congress Experience, Detroit, 4-6 April 2017.